@conference{Pandey2022,
title = {Empirical Analysis of Bi-directional Wi-Fi Network Performance on Mobile Robots in Indoor Environments},
author = {Pranav Pandey and Ramviyas Parasuraman},
url = {Preprint: https://arxiv.org/pdf/2110.03011.pdf
Codes: https://github.com/herolab-uga/ros-network-analysis
Paper: https://ieeexplore.ieee.org/abstract/document/9860438},
doi = {10.1109/VTC2022-Spring54318.2022.9860438},
year = {2022},
date = {2022-06-22},
booktitle = {2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)},
pages = {1-7},
publisher = {IEEE},
abstract = {This paper proposes a framework to measure the important metrics (throughput, delay, packet retransmits, signal strength, etc.) to determine Wi-Fi network performance of mobile robots supported by the Robot Operating Systems (ROS) middleware. We analyze the bidirectional network performance of mobile robots through an experimental setup in an indoor environment, where a mobile robot is communicating vital sensor data such as video streaming from the camera(s) and LiDAR scan values to a command station while it navigates an indoor environment through teleoperated velocity commands received from the command station. The experiments evaluate the performance under 2.4 GHz and 5 GHz channels with different placement of Access Points (AP) with up to two network devices on each side. The framework is generalizable to vehicular network evaluation and the discussions and insights from this study apply to the field robotics community, where the wireless network plays a key role in enabling the success of robotic missions in real-world environments.},
keywords = {evaluation, networking, robotics},
pubstate = {published},
tppubtype = {conference}
}

@article{Parasuraman2018b,
title = {Multi-Point Rendezvous in Multi-Robot Systems},
author = {Ramviyas Parasuraman and Jonghoek Kim and Shaocheng Luo and Byung-Cheol Min},
url = {https://ieeexplore.ieee.org/document/8472798},
doi = {10.1109/TCYB.2018.2868870},
isbn = {2168-2275},
year = {2020},
date = {2020-01-01},
journal = {IEEE Transactions on Cybernetics},
volume = {50},
number = {1},
pages = {310-323},
abstract = {Multi-robot rendezvous control and coordination strategies have garnered significant interest in recent years because of their potential applications in decentralized tasks. In this paper, we introduce a coordinate-free rendezvous control strategy to enable multiple robots to gather at different locations (dynamic leader robots) by tracking their hierarchy in a connected interaction graph. A key novelty in this strategy is the gathering of robots in different groups rather than at a single consensus point, motivated by autonomous multi-point recharging and flocking control problems. We show that the proposed rendezvous strategy guarantees convergence and maintains connectivity while accounting for practical considerations such as robots with limited speeds and an obstacle-rich environment. The algorithm is distributed and handles minor faults such as a broken immobile robot and a sudden link failure. In addition, we propose an approach that determines the locations of rendezvous points based on the connected interaction topology and indirectly optimizes the total energy consumption for rendezvous in all robots. Through extensive experiments with the Robotarium multi-robot testbed, we verified and demonstrated the effectiveness of our approach and its properties.},
keywords = {control, herding, multi-robot systems, robotics},
pubstate = {published},
tppubtype = {article}
}

@conference{Yang2020b,
title = {Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions},
author = {Qin Yang and Ramviyas Parasuraman},
url = {https://arxiv.org/abs/2009.00288},
year = {2020},
date = {2020-11-06},
booktitle = {2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2020)},
abstract = {This paper focuses on the teaming aspects and the role of heterogeneity in a multi-robot system applied to robot-aided urban search and rescue (USAR) missions. We specifically propose a needs-driven multi-robot cooperation mechanism represented through a Behavior Tree structure and evaluate the performance of the system in terms of the group utility and energy cost to achieve the rescue mission
in a limited time. From the theoretical analysis, we prove that the needs-drive cooperation in a heterogeneous robot system enables higher group utility compared to a homogeneous robot system. We also perform simulation experiments to verify the proposed needs-driven cooperation and show that the heterogeneous multi-robot cooperation can achieve better performance and increase system robustness
by reducing uncertainty in task execution. Finally, we discuss the application to human-robot teaming.},
keywords = {human-robot interaction, multi-robot-systems, robotics},
pubstate = {published},
tppubtype = {conference}
}

@conference{Kannan2020,
title = {Material Mapping in Unknown Environments using Tapping Sound},
author = {Shyam Sundar Kannan and Wonse Jo and Ramviyas Parasuramanoiuytrewq and Byung-Cheol Min},
year = {2020},
date = {2020-10-29},
booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020)},
abstract = {In this paper, we propose an autonomous exploration and tapping mechanism-based material mapping system for a mobile robot in unknown environments. The proposed system integrates SLAM modules and sound-based material classification to enable a mobile robot to explore an unknown environment autonomously and at the same time identify the various objects and materials in the environment in an efficient manner, creating a material map which localizes the various materials in the environment over the occupancy grid. A tapping mechanism and tapping audio signal processing based on machine learning techniques are exploited for a robot to identify the objects and materials. We demonstrate the proposed system through experiments using a mobile robot platform installed with Velodyne LiDAR, a linear solenoid, and microphones in an exploration-like scenario with various materials. Experiment results demonstrate that the proposed system can create useful material maps in unknown environments.},
keywords = {mapping, perception, robotics},
pubstate = {published},
tppubtype = {conference}
}

@conference{Parashar2020,
title = {Particle Filter Based Localization of Access Points Using Direction of Arrival on Mobile Robots},
author = {Ravi Parashar and Ramviyas Parasuraman},
url = {http://hero.uga.edu/wp-content/uploads/2020/07/ArXiv_VTCW_2020_Parashar.pdf},
year = {2020},
date = {2020-10-05},
booktitle = {The 2020 IEEE 92nd Vehicular Technology Conference: VTC2020-Fall },
abstract = {Localization of autonomous vehicles in unknown and unstructured GPS-denied environments is still a relevant and major research challenge in the field of Robotics. Applications of such research can be found in search and rescue missions and connected vehicles, where multiple robots need an efficient solution for simultaneous localization through multi-sensor integration so that they can effectively cooperate and coordinate tasks amongst themselves. In this paper, we propose a novel method for estimating the position of a WiFi access point in relation to a moving robot. Specifically, we exploit the integration of two sensors: Direction-of-arrival (DOA) of WiFi signals and the robot's odometry and combine them with Gaussian probabilistic sampling in a Particle Filter framework. We evaluate the proposed method in terms of accuracy and computational efficiency through extensive trials on datasets gathered from real-world measurements with mobile robots and compared our method against standard approaches. The results demonstrate superior localization accuracy (up to 3x improvement) and capability for most practical applications.
},
keywords = {localization, networking, robotics},
pubstate = {published},
tppubtype = {conference}
}

@workshop{Tahir2020,
title = {Robot Controlling Robots - A New Perspective to Bilateral Teleoperation in Mobile Robots},
author = {Nazish Tahir and Ramviyas Parasuraman},
url = {https://ankitbhatia.github.io/reacting_contact_workshop/},
year = {2020},
date = {2020-07-12},
booktitle = {RSS 2020 Workshop on Reacting to Contact: Enabling Transparent Interactions through Intelligent Sensing and Actuation},
abstract = {Adaptation to increasing levels of autonomy - from manual teleoperation to complete automation is of particular interest to Field Robotics and Human-Robot Interaction community. Towards that line of research, we introduce and investigate a novel bilaterally teleoperation control strategy for a robot to the robot system. A bilateral teleoperation scheme is typically applied to human control of robots. In this abstract, we look at a different perspective of using a bilateral teleoperation system between robots, where one robot (Labor) is teleoperated by an autonomous robot (Master). To realize such a strategy, our proposed robot-system is divided into a master-labor networked scheme where the master robot is located at a remote site operable by a human user or an autonomous agent and a labor robot; the follower robot is located on operation site. The labor robot is capable of reflecting the odometry commands of the master robot meanwhile also navigating its environment by obstacle detection and avoidance mechanism. An autonomous algorithm such as a typical SLAM-based path planner is controlling the master robot, which is provided with a suitable force feedback informative of the labor response by its interaction with the environment. We perform preliminary experiments to verify the system feasibility and analyze the motion transparency in different scenarios. The results show promise to investigate this research further and develop this work towards human multi-robot teleoperation.},
keywords = {control, human-robot interaction, networking, robotics},
pubstate = {published},
tppubtype = {workshop}
}

@article{Haseeb2018,
title = {Wisture: Touch-less Hand Gesture Classification in Unmodified Smartphones Using Wi-Fi Signals},
author = {Mohamed Haseeb and Ramviyas Parasuraman},
url = {https://ieeexplore.ieee.org/document/8493572},
doi = {10.1109/JSEN.2018.2876448},
year = {2019},
date = {2019-01-01},
journal = { IEEE Sensors Journal},
volume = {19},
number = {1},
pages = {257-267},
abstract = {This paper introduces Wisture, a new online machine learning solution for recognizing touch-less dynamic hand gestures on a smartphone. Wisture relies on the standard Wi-Fi Received Signal Strength (RSS) using a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN), thresholding filters and traffic induction. Unlike other Wi-Fi based gesture recognition methods, the proposed method does not require a modification of the smartphone hardware or the operating system, and performs the gesture recognition without interfering with the normal operation of other smartphone applications. We discuss the characteristics of Wisture, and conduct extensive experiments to compare its performance against state-of-the-art machine learning solutions in terms of both accuracy and time efficiency. The experiments include a set of different scenarios in terms of both spatial setup and traffic between the smartphone and Wi-Fi access points (AP). The results show that Wisture achieves an online recognition accuracy of up to 94% (average 78%) in detecting and classifying three hand gestures.},
keywords = {networking, perception, robotics},
pubstate = {published},
tppubtype = {article}
}

@article{Tardioli2018,
title = {Pound: A multi-master ROS node for reducing delay and jitter in wireless multi-robot networks},
author = {Danilo Tardioli and Ramviyas Parasuraman and Petter Ögren. },
url = {https://www.sciencedirect.com/science/article/pii/S0921889017309144},
doi = {10.1016/j.robot.2018.10.009},
year = {2019},
date = {2019-01-01},
journal = {Robotics and Autonomous Systems},
volume = {111},
pages = {73-87},
abstract = {The Robot Operating System (ROS) is a popular and widely used software framework for building robotics systems. With the growth of its popularity, it has started to be used in multi-robot systems as well. However, the TCP connections that the platform relies on for connecting the so-called ROS nodes presents several issues regarding limited-bandwidth, delays, and jitter, when used in wireless multi-hop networks. In this paper, we present a thorough analysis of the problem and propose a new ROS node called Pound to improve the wireless communication performance by reducing delay and jitter in data exchanges, especially in multi-hop networks. Pound allows the use of multiple ROS masters (roscores), features data compression, and importantly, introduces a priority scheme that allows favoring more important flows over less important ones. We compare Pound to the state-of-the-art solutions through extensive experiments and show that it performs equally well, or better in all the test cases, including a control-over-network example.},
keywords = {multi-robot, networking, robotics},
pubstate = {published},
tppubtype = {article}
}

@article{Parasuraman2018c,
title = {Special Issue on “Assistive Robotics”},
author = {Ramviyas Parasuraman and Byung-Cheol Min},
url = {https://www.mdpi.com/2227-7080/6/4/95},
doi = {10.3390/technologies6040095},
year = {2018},
date = {2018-10-20},
abstract = {The technology behind robotics has rapidly advanced to a level enabling humans and robots to interact in everyday aspects of life. Nevertheless, it remains a challenge to design and develop these interactions to accommodate people of varying abilities [1]. Assistive Robotics is a branch of robotics that addresses the research challenges inherent in providing sensory and perception abilities and performing actions that are beneficial to the elderly and physically-challenged people [2,3]. This Special Issue presents recent research advances in the field of Assistive Robotics that can empower people to perform various tasks they could not otherwise, to be more independent, and to improve their overall quality of life. Robots for the visually impaired, telepresence robots for physical impairments, social robots for cognitive impairments, and wearable robots are some of the areas of research that were welcomed in this special issue.},
keywords = {assistive devices, robotics},
pubstate = {published},
tppubtype = {article}
}

@conference{Parasuraman2018,
title = {Consensus Control of Distributed Robots Using Direction of Arrival of Wireless Signals},
author = {Ramviyas Parasuraman and Byung-Cheol Min.},
url = {https://www.youtube.com/watch?v=6BkFrJ8vceg&feature=youtu.be},
year = {2018},
date = {2018-10-15},
abstract = {In multi-robot applications, consensus control and coordination are vital and potentially repetitive tasks. To circumvent practical limitations such as a global localization system, researchers have focused on bearing-based consensus controllers, but most assumed that measurements from sensors (e.g. vision) are noise-free. In this paper, we propose to use wireless signal measurements to estimate the direction of arrival (relative bearings) of neighboring robots and introduce a weighted bearing consensus controller to achieve coordinate-free distributed multi-robot rendezvous. We prove that the proposed controller guarantees connectivity maintenance and convergence even in the presence of measurement noise. We conduct extensive numerical simulation experiments using the Robotarium multi-robot platform to verify and demonstrate the properties of the proposed controller and to compare the performance of the rendezvous task against several state-of-the-art rendezvous controllers.},
keywords = {control, multi-robot, networking, robotics},
pubstate = {published},
tppubtype = {conference}
}

@conference{Parasuraman2018d,
title = {Kalman filter based spatial prediction of wireless connectivity for autonomous robots and connected vehicles},
author = {Ramviyas Parasuraman, Petter Ögren, Byung-Cheol Min},
url = {https://www.researchgate.net/publication/326235283_Kalman_Filter_Based_Spatial_Prediction_of_Wireless_Connectivity_for_Autonomous_Robots_and_Connected_Vehicles},
year = {2018},
date = {2018-08-27},
abstract = {This paper proposes a new Kalman filter based online framework to estimate the spatial wireless connectivity in terms of received signal strength (RSS), which is composed of path loss and the shadow fading variance of a wireless channel in autonomous vehicles. The path loss is estimated using a localized least squares method and the shadowing effect is predicted with an empirical (exponential) variogram. A discrete Kalman Filter is used to fuse these two models into a statespace formulation. The approach is unique in a sense that it is online and does not require the exact source location to be known apriori. We evaluated the method using real-world measurements dataset from both indoors and outdoor environments. The results show significant performance improvements compared to state-of-the-art methods using Gaussian processes or Kriging interpolation algorithms. We are able to achieve a mean prediction accuracy of up to 96% for predicting RSS as far as 20 meters ahead in the robot s trajectory.},
keywords = {networking, robotics},
pubstate = {published},
tppubtype = {conference}
}